A Method Using Multiple Models To Superresolve SAR Imagery

This paper introduces a methodology for the superresolution of synthetic aperture radar (SAR) images using multiple target and clutter models. The system has two major components: a mechanism that selects the appropriate model for superresolution and a bank of model estimators to accomplish the superresolution. The typical point scatterer model is incorporated into this technique as well as a model for clutter. Other models can be naturally incorporated. This methodology is flexible in that it can utilize many of the well-known modern spectral estimation techniques. The ability to more accurately model targets using models other than the point scatterer as well as the importance of including models for clutter into a superresolution paradigm is addressed. These issues are shown to be relevant to the automatic target recognition / detection (ATR/D) problem. We present a comparison of our technique with other SAR imaging methods and discuss the relative benefits afforded by such an approach.